Under the Weather

Earthquakes, hurricanes, tornadoes, blizzards, ice storms, flooding, power outages, extreme heat, freezing cold, even volcanic eruptions, you name it — chances are your department has experienced a number of extreme weather events. Think about your last severe weather event. You probably remember — “Yeah, we were busy”. Or maybe….“it took longer to get there”.

Lets start exploring how we can use data to not only back these statements up, but start quantifying the impact of weather on performance.

Background

Most CAD or RMS systems do not natively capture weather data, so any weather analysis requires extensive data manipulation, curation, table joining, and purchasing weather data from third-party providers. Fortunately, NFORS takes away all these pains by automatically capturing and saving weather details for every incoming incident. The weather attributes collected include temperature, wind speed, wind gust, humidity, precipitation intensity, precipitation accumulation, and even textual summaries. Thanks to our third-party provider, DarkSky, we also populate weather on historic data, regardless of when you joined NFORS!

Impact on Call Volume

For the first visualization exercise, lets explore the relationship between extreme cold temperatures and call volume over time.

Extreme Temperatures and Call Volume

1. Create a new Line visualization, using your incidents index
2. Adjust top time range to a longer time range, such as 2 years
3. Click Add metrics
4. Select Y-Axis
5. For aggregation, select Min, because we are visualizing minimum temperature
6. For field, type/select weather.currently.temperature, corresponding to the temperature at event time
7. Add a custom label of Min Temp
8. Under Buckets, select Date Histogram
9. Add a custom label of Time
10. Change to the Metrics & Axes tab
11. Expand the Min Temp section
12. On Value Axis, select a new axis, Right-Axis 1
13. Press the play button

Look at your results closely. Are there peaks or trends visible? For this department, we can see an extreme cold during the first week of 2018:

Peak in Extreme Temperature

And a corresponding peak in call volume:

Peak In Call Volume

Going Further

Extreme weather will likely affect a subset of call types more than the entire dataset. For example, such as in this case, cold weather will significantly affect the number of fire alarms, utility incidents (due to bursting pipes), and possibly car accidents due to treacherous road conditions. Other extreme events, such as heat waves, might not see the same extreme peaks in overall call volumes, but just an increase in a particular subset of EMS conditions such as heat strokes or dehydration. We recommend applying type, subtype, or category filters directly on visualizations or combining with existing dashboard visualizations to encourage deeper exploration.

Other Extremes

Temperature isn’t the only variable we may want to look at. How about max snow accumulation or wind speed?

For those of you in Florida, you may want to explore the impacts of hurricanes such as Hurricane Irma, which nearly doubled call volume for a week, in September, 2017.

Wind Gust vs Call Volume (spike corresponds to Hurricane Irma)

Impact on Response Times

When analyzing weather, do not be restricted to simply the impact on call volume. Impassable roads, reduced visibility, and simply driving at safer, slower speeds in bad weather conditions also affects response times. Here’s another simple visualization that compares the daily weather summary to response time.

Weather Impact on Response Time

1. Create a new Horizontal Bar visualization, using your incidents index
2. Adjust top time range to a longer time range, such as 2 years
3. Change the Metric to Percentile
4. Set the field to durations.travel.minutes
5. Remove all other percentiles, and change 99 to 90
6. Add a custom label of Travel Time
7. Under Buckets, select X-Axis
8. Select Terms
9. Type/select weather.currently.icon, which represents the weather category, or representative visual icon, at event time
10. Add a custom label of Weather
11. Change Size to 25, to ensure all weather categories are represented
12. Change to the Panel Settings tab, and click Order Buckets By Sum
13. Press the play button

Travel Times in Different Weather Conditions

As expected, you may see slower travel times in adverse conditions such as snow, sleet, and rain. For this department, we see more than a 40% increase in travel times in sleet conditions when compared to the norm of cloudy/clear times.

The first step in preparing for the next weather event is understanding how the weather has impacted YOUR department in the past. Every department is impacted by weather differently, due to a number of controllable and uncontrollable factors including severity of the weather, geospatial features, and overall department readiness. The only way to quantify this impact, is to dive deep and start exploring your own data with exploration, visualizations, and detailed data analysis. We’re excited to hear your success stories, and we’re always hear to help! Reach out to us for questions, thoughts, or to simply showcase your own visualization and weather insights with the rest of the NFORS community.